Triple

T15678725
Position Surface form Disambiguated ID Type / Status
Subject Praise (novel) E377514 entity
Predicate followsCharacter P10688 FINISHED
Object Cynthia E48557 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Cynthia | Statement: [Praise (novel), followsCharacter, Cynthia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cynthia
Context triple: [Praise (novel), followsCharacter, Cynthia]
  • A. Cynthia chosen
    Cynthia is a common feminine given name used in various cultures, often associated with the Greek moon goddess Artemis.
  • B. Cindy
    Cindy is a fictional character from the short-lived 1970s American sitcom "Blansky's Beauties," which followed the lives of Las Vegas showgirls.
  • C. Cindy
    Cindy is a fictional character from the action film "Commando," appearing as part of the movie’s high-stakes rescue storyline.
  • D. Carmyne
    Carmyne is a given name, typically a variant spelling of Carmine, used for both males and females.
  • E. Renee
    Renee is a feminine given name of French origin, commonly used in English- and French-speaking countries.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f2f1640819086efd5a73bb9734a completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ee0446881909e9c2504d51d49a3 completed May 9, 2026, 5:29 p.m.
Created at: April 10, 2026, 4:16 a.m.